Zhen Y Wang
National Institutes of Health
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Featured researches published by Zhen Y Wang.
Nature Genetics | 2007
Matthew D. Mailman; Michael Feolo; Yumi Jin; Masato Kimura; Kimberly A Tryka; Rinat Bagoutdinov; Luning Hao; Anne Kiang; Justin Paschall; Lon Phan; Natalia Popova; Stephanie Pretel; Lora Ziyabari; Moira Lee; Yu Shao; Zhen Y Wang; Karl Sirotkin; Minghong Ward; Michael Kholodov; Kerry Zbicz; Jeff Beck; Michael Kimelman; Sergey Shevelev; Don Preuss; Eugene Yaschenko; Alan S. Graeff; James Ostell; Stephen T. Sherry
The National Center for Biotechnology Information has created the dbGaP public repository for individual-level phenotype, exposure, genotype and sequence data and the associations between them. dbGaP assigns stable, unique identifiers to studies and subsets of information from those studies, including documents, individual phenotypic variables, tables of trait data, sets of genotype data, computed phenotype-genotype associations, and groups of study subjects who have given similar consents for use of their data.
BMC Medical Genetics | 2007
L. Adrienne Cupples; Heather T Arruda; Emelia J. Benjamin; Ralph B. D'Agostino; Serkalem Demissie; Anita L. DeStefano; Josée Dupuis; Kathleen Falls; Caroline S. Fox; Daniel J. Gottlieb; Diddahally R. Govindaraju; Chao-Yu Guo; Nancy L. Heard-Costa; Shih-Jen Hwang; Sekar Kathiresan; Douglas P. Kiel; Jason M. Laramie; Martin G. Larson; Daniel Levy; Chunyu Liu; Kathryn L. Lunetta; Matthew D Mailman; Alisa K. Manning; James B. Meigs; Joanne M. Murabito; Christopher Newton-Cheh; George T. O'Connor; Christopher J. O'Donnell; Mona Pandey; Sudha Seshadri
BackgroundThe Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies.MethodsAdult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests.ResultsThe participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 ± 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency ≥ 10%, genotype call rate ≥ 80%, Hardy-Weinberg equilibrium p-value ≥ 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.ConclusionWe have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.
Nucleic Acids Research | 2014
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Zhen Y Wang; Lora Ziyabari; Moira Lee; Natalia Popova; Nataliya Sharopova; Masato Kimura; Michael Feolo
The Database of Genotypes and Phenotypes (dbGap, http://www.ncbi.nlm.nih.gov/gap) is a National Institutes of Health-sponsored repository charged to archive, curate and distribute information produced by studies investigating the interaction of genotype and phenotype. Information in dbGaP is organized as a hierarchical structure and includes the accessioned objects, phenotypes (as variables and datasets), various molecular assay data (SNP and Expression Array data, Sequence and Epigenomic marks), analyses and documents. Publicly accessible metadata about submitted studies, summary level data, and documents related to studies can be accessed freely on the dbGaP website. Individual-level data are accessible via Controlled Access application to scientists across the globe.
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo
Archive | 2013
Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Masato Kimura; Zhen Y Wang; Lora Ziyabari; Moira Lee; Michael Feolo